For the final project in my Computer Vision class (ECE 5554), I decided that the children’s book Where’s Waldo needed to be solved. For good. All those countless hours spent searching for the red and white striped man could be best spent elsewhere. You know, like solving mazes in Highlights.

After some research, I decided that I could construct a Hidden Markov Model based on the 2-dimensional Discrete Cosine Transform (2D DCT) of our friend, Waldo. Using the model, we could scan through a much larger image, looking for sections that closely match the model of Waldo. If the match is close enough (i.e. over a threshold), then highlight that section blue. We can play with the threshold to make the identification better or worse. With the test images, we saw a 70% positive detection of Waldo. Just think, with a few more algorithm and speed optimizations, manually solving for that elusive figure will be a thing of the past!

You can find the report and MATLAB code below. The code is based on the HMM Toolbox.